Load Model and Data
# Load Model
source("almond_yield_anomoly.R")
# Load Data
data <- read_delim("clim.txt", delim = " ", col_names = TRUE, quote = "") %>%
# Clean column names
clean_names()
Run Model
# Run Model
almond_yield_anomaly_from_daily(data)
## # A tibble: 22 × 3
## water_year avg_min_temp_c total_precip_mm
## <dbl> <dbl> <dbl>
## 1 1989 8.64 2.80
## 2 1990 8.68 55.8
## 3 1991 10.4 135.
## 4 1992 11.9 69.6
## 5 1993 10.9 77.9
## 6 1994 9.62 34.8
## 7 1995 12.6 677.
## 8 1996 12.0 40.3
## 9 1997 9.99 285.
## 10 1998 11.5 89.8
## # ℹ 12 more rows
## $yield_anomalies
## 1989 1990 1991 1992 1993 1994
## -0.3552237 9.2906757 68.9130633 15.4280698 20.2083803 2.4820009
## 1995 1996 1997 1998 1999 2000
## 1919.9811511 3.5818399 329.6938750 27.8636956 -0.1436364 9.5999883
## 2001 2002 2003 2004 2005 2006
## 159.5119587 0.2450914 -0.2585997 -0.2367722 656.3724121 18.6324135
## 2007 2008 2009 2010
## 20.2007396 576.2821943 0.7367438 153.7655092
##
## $mean_yield_anomaly
## [1] 181.4453
##
## $max_yield_anomaly
## [1] 1919.981
##
## $min_yield_anomaly
## [1] -0.3552237
# Save results
almond <- almond_yield_anomaly_from_daily(data)
## # A tibble: 22 × 3
## water_year avg_min_temp_c total_precip_mm
## <dbl> <dbl> <dbl>
## 1 1989 8.64 2.80
## 2 1990 8.68 55.8
## 3 1991 10.4 135.
## 4 1992 11.9 69.6
## 5 1993 10.9 77.9
## 6 1994 9.62 34.8
## 7 1995 12.6 677.
## 8 1996 12.0 40.3
## 9 1997 9.99 285.
## 10 1998 11.5 89.8
## # ℹ 12 more rows
# View results (in tons/acre)
almond$min_yield_anomaly
## [1] -0.3552237
almond$mean_yield_anomaly
## [1] 181.4453
almond$max_yield_anomaly
## [1] 1919.981
